(1) Field of Invention
The present invention relates to a system for improving the performance of a video object recognition system and, more particularly, to a system for improving the performance of a video object recognition system using a pseudo-tracklet approach.
(2) Description of Related Art
In previous bio-inspired video-based object recognition systems, locations in video images containing potential objects of interests (moving or stationary) are first detected using a bio-inspired detection approach, such as visual saliency, and then the regions of interest (ROI) around the detections are passed to a recognition engine. In this type of system, there is no tracking front-end for detection, which greatly reduces system complexity, but also puts much more burden on the recognition engine for accurate classification of objects over time. As a result, the recognition system output for a single object in the scene can fluctuate from frame to frame, sometimes giving erroneous classifications for the object or missing the object entirely if the detection system fails, resulting in poor system recognition performance.
The method described above exhibits limitations that make it incomplete. Thus, a continuing need exists for a system for improving the overall system performance of an object recognition system without a full-featured front-end tracking system, background clutter, and ambiguous classification resulting from imperfect classifier training.